A comparative study of game theoretic and evolutionary models of bargaining for software agents

被引:52
作者
Fatima, SS [1 ]
Wooldridge, M
Jennings, NR
机构
[1] Univ Liverpool, Dept Comp Sci, Liverpool L69 3BX, Merseyside, England
[2] Univ Southampton, Sch Elect & Comp Sci, Southampton SO17 1BJ, Hants, England
基金
英国工程与自然科学研究理事会;
关键词
bargaining; e-commerce; evolutionary algorithms; game theory; software agents;
D O I
10.1007/s10462-004-6391-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];
摘要
Most of the existing work in the study of bargaining behavior uses techniques from game theory. Game theoretic models for bargaining assume that players are perfectly rational and that this rationality is common knowledge. However, the perfect rationality assumption does not hold for real-life bargaining scenarios with humans as players, since results from experimental economics show that humans find their way to the best strategy through trial and error, and not typically by means of rational deliberation. Such players are said to be boundedly rational. In playing a game against an opponent with bounded rationality, the most effective strategy of a player is not the equilibrium strategy but the one that is the best reply to the opponent's strategy. The evolutionary model provides a means for studying the bargaining behaviour of boundedly rational players. This paper provides a comprehensive comparison of the game theoretic and evolutionary approaches to bargaining by examining their assumptions, goals, and limitations. We then study the implications of these differences from the perspective of the software agent developer.
引用
收藏
页码:185 / 203
页数:19
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